1. Field of the Invention
The present invention relates generally to an apparatus and method to model mammalian respiratory systems, whereby appropriate computational processing of the estimated component values for such a model can serve as parametric means for detection, diagnosis and treatment of various pathologies.
2. Description of the Prior Art
Pulmonary function tests, spirometry measurements, and lung volume measurements are all examples of various existing alternatives administered for the purposes of testing and assessing human lung conditions. These tests are often useful in diagnosing certain types of lung disease, especially asthma, bronchitis, and emphysema. They are also used after the administration of medications to assess their effect, and to measure progress in a disease treatment. Traditionally, lung function is most commonly assessed by standard spirometric pulmonary function tests. However, spirometric measurements require maximal coordinated inspiratory and expiratory efforts by the tested subject. Such considerable degree of cooperation required from the subject makes spirometry inappropriate for young children and older adults. In contrast, respiratory function assessment by the method of forced oscillation requires minimal patient cooperation, namely wearing a nose clip to close the nares and breathing normally through the mouth. Air pressure and rate of air flow at the entrance to the respiratory system are measured, thereby defining its mechanical impedance. In particular, the Impulse Oscillometry System (IOS) is a commercially available product for measuring respiratory impedance by employing brief (60-70 milliseconds) pulses of pressure using a loudspeaker. IOS measurements yield frequency-dependent impedance curves that, in clinical practice today, are inspected to identify changes in shape, or course, and magnitude from those produced in a healthy state.
The impedance curves (one representing the complex impedance's real part referred to as respiratory resistance Zr, and the other representing the impedance's imaginary part referred to as respiratory reactance Zx) yielded from the IOS measurements are also readily amenable to engineering analysis, and may be correlated with models consisting of electrical components that are analogous to the resistances, compliances and inertances inherent in the respiratory system. With appropriate computational processing, the estimated component values for such respiratory system models can be used as parametric means for better detection, diagnosis and treatment of various pathologies. There are four well-known (linear) models of the human respiratory system, of the type discussed above, each of which seeks to provide an accurate circuit that mimics results obtained from a subject. These models, namely the RIC, viscoelastic, DuBois and Mead models, have been documented extensively in literature, and are summarized as the following:
RIC model—The resistance of the airways R, lung inertance I, and the compliance of the alveoli C, are modeled as a simple three element circuit (with R typically in cmH2O/L/s or kPa/L/s, I in cmH2O/L/s2 or kPa/L/s2, and C in L/cmH2O or L/kPa). See FIG. 3.
Viscoelastic model —The viscoelastic model parameterizes the respiratory system based on overall airway resistance Raw, static compliance Cs, and viscoelastic tissue resistance and compliance, Rve and Cve, respectively. See FIG. 11.
DuBois model —This model divides the resistance, inertance and compliance properties into separate parameters for the airway and tissue resistance (Raw, Rt) components. Thus the model includes separate parameters for inertance (Iaw, It), and alveolar and tissue compliance (Cg, Ct). See FIG. 4.
Mead model —Mead's model simulates different mechanics in the lung and chest wall. Its seven parameters are inertance (I), central and peripheral resistance (Rc and Rp), and lung, chest wall, bronchial tube, and extrathoracic compliance (Cl, Cw, Cb, Ce). See FIG. 5.
For each of the above models, values for that model's parameters needed to be determined to minimize the difference between measured impedance data (at discrete frequencies) and the impedance produced by those model parameter values. This optimization procedure is referred to as parameter estimation, which is similar in concept to curve-fitting. Error criteria that are commonly used in parameter estimation problems include least absolute value (LAV), least squares (LS), minimax, and maximum likelihood.
In the patent literature, U.S. Pat. No. 6,068,602, to Tham et al., includes a discussion of electrical circuit models of mammalian respiratory systems including a method and apparatus for determining airway resistance and lung compliance. More specifically, Tham et al. teach the use of electrical circuit models wherein at least one component parameter is non-linear. The system non-intrusively obtains pressure and flow data signals from a pressure transducer and a laminar flow element without interrupting or interfering with normal breathing and gas supply to a patient. An invariant exponential is determined empirically based on physical characteristics of the airway. The non-linear airway resistance and lung compliance can then be calculated based on the sensed flow rate, gas pressure, a calculated gas volume, and the invariant exponential using linear techniques.
However, despite current progress in the field of respiratory analysis, such as that taught in the Tham et al. reference, there is a continuing need to provide reliable circuit models capable of accurately simulating the respiration system of a subject.
A need exists for an improved circuit model that further minimizes the differences between the measured impedance data and the impedance produced by the model parameter values.
A need also exists for a method of analyzing a subject's air pressure and air flow that is non-invasive and easily administered to subjects of all ages and health.